NCI Investigator on the Results of a Study Exploring Sex Bias Related to TMB as a Biomarker of PD-1 Inhibitors

Audrey Sternberg

CancerNetwork® spoke with Sanju Sinha of the National Cancer Institute about the resulting data from his research into sex differences associated with using tumor mutational burden to predict response to PD-1 inhibition.

CancerNetwork® sat down with Sanju Sinha, a PhD candidate who works with computational biologist Eytan Ruppin, MD, PhD, at the National Cancer Institute, to discuss an abstract presented at the recent American Association for Cancer Research (AACR) Annual Meeting 2021 on tumor mutational burden (TMB) as a biomarker for PD-1 inhibition. He and his team determined that in certain tumor types, the effect of TMB on therapy response varied between genders.

Transcription:

There are primarily 3 takeaways from our study, and it is important to note them in order. We first observed that, in melanoma, there is a marked difference between the survival between these 2 groups of low versus high TMB in males versus females. Specifically, TMB is able to stratify the responders in female patients but not able to stratify these responders in male patients. This is the first record.

The second takeaway is that we found no such differences in lung cancer, even though we had quite a large [number of patients with lung cancer]. The third takeaway is that we, indeed, found such differences, then we extended analysis to [seven] different cancer types. And these differences, very specifically, are present in 2 cancer types, glioblastoma and cancer of unknown origin. However, we must note that these differences [were recorded with an] effect size that is not significant. We do need to still repeat this analysis. We are actually encouraging other researchers to repeat this analysis in different large, independent cohorts.

Reference

Sinha N, Sinha S, Cheng K, et al. The recently approved high-TMB criteria may introduce a sex bias in response to PD1 inhibitors. Presented at: AACR Annual Meeting 2021; April 10-15, 2021; virtual. Abstract 29.